Smart encounters

Abstract

Systems and methods for providing content recommendations to a user based on aggregate profile data of other users that the user is predicted to encounter in the future are disclosed. In general, an aggregate profile is obtained for a predicted encounter of a first user. The aggregate profile is based on user profiles of a number of second users identified for the predicted encounter. In one embodiment, the predicted encounter is a predicted physical encounter. In another embodiment, the predicted encounter is a predicted remote encounter. One or more content recommendations are then obtained for the first user based on the aggregate profile for the predicted encounter. The content recommendation may be, for example, a recommended movie, a recommended television program, a recommended news article, a recommended user-generated video (e.g., a recommended video on YouTube.com), or the like.

What is claimed is: 
     
         1 . A method of operating a computing device comprising:
 obtaining an aggregate profile for a predicted encounter of a first user, the aggregate profile being based on user profiles of a plurality of second users identified for the predicted encounter of the user; and   obtaining one or more content recommendations for the first user based on the aggregate profile for the predicted encounter.   
     
     
         2 . The method of  claim 1  wherein the predicted encounter is a predicted physical encounter. 
     
     
         3 . The method of  claim 2  wherein the predicted physical encounter is predicted based on a historical record of a location of the first user and historical records of locations of the plurality of second users. 
     
     
         4 . The method of  claim 3  wherein the predicted physical encounter is predicted by:
 predicting a future location of the first user based on the historical record of the location of the first user; 
 predicting one or more future locations for each of at least a subset of a plurality of known users based on historical records of locations of the at least a subset of the plurality of known users; and 
 identifying ones of the at least a subset of the plurality of known users having future locations that overlap the future location of the first user as the plurality of second users for the predicted physical encounter. 
 
     
     
         5 . The method of  claim 2  wherein the predicted physical encounter is predicted based on a schedule of the first user. 
     
     
         6 . The method of  claim 2  wherein the predicted physical encounter is predicted based on schedules of the plurality of second users. 
     
     
         7 . The method of  claim 2  wherein the predicted physical encounter is predicted based on schedules of the first user and the plurality of second users. 
     
     
         8 . The method of  claim 1  wherein the predicted encounter is a predicted remote encounter. 
     
     
         9 . The method of  claim 8  wherein the predicted remote encounter is predicted based on a schedule of the first user. 
     
     
         10 . The method of  claim 8  wherein the predicted remote encounter is predicted based on schedules of the plurality of second users. 
     
     
         11 . The method of  claim 8  wherein the predicted physical encounter is predicted based on schedules of the first user and the plurality of second users. 
     
     
         12 . The method of  claim 1  wherein the aggregate profile for the predicted encounter comprises one or more keywords, and obtaining the one or more content recommendations comprises obtaining the one or more content recommendations based on at least one of the one or more keywords. 
     
     
         13 . The method of  claim 12  wherein the aggregate profile for the predicted encounter further comprises a number of user matches for each of the one or more keywords. 
     
     
         14 . The method of  claim 13  wherein the one or more keywords is a plurality of keywords, and obtaining the one or more content recommendations comprises obtaining a plurality of content recommendations based on the plurality of keywords and the number of user matches for each of the plurality of keywords. 
     
     
         15 . The method of  claim 14  wherein a number of the plurality of content recommendations that match each keyword of the plurality of keywords is a function of the number of user matches for the keyword. 
     
     
         16 . The method of  claim 13  wherein the one or more keywords is a plurality of keywords, and obtaining the one or more content recommendations comprises obtaining the one or more content recommendations based on one or more of the plurality of keywords having a highest number of user matches. 
     
     
         17 . The method of  claim 12  wherein the aggregate profile for the predicted encounter further comprises a ratio of a number of user matches to a total number of users in the plurality of second users for each of the one or more keywords. 
     
     
         18 . The method of  claim 17  wherein the one or more keywords is a plurality of keywords, and obtaining the one or more content recommendations comprises obtaining a plurality of content recommendations based on the plurality of keywords and the ratio of the number of user matches to the total number of users for each of the plurality of keywords. 
     
     
         19 . The method of  claim 18  wherein a number of the plurality of content recommendations that match each keyword of the plurality of keywords is a function of the ratio of the number of user matches to the total number of users for the keyword. 
     
     
         20 . The method of  claim 17  wherein the one or more keywords is a plurality of keywords, and obtaining the one or more content recommendations comprises obtaining the one or more content recommendations based on one or more of the plurality of keywords having a highest ratio of the number of user matches to the total number of users. 
     
     
         21 . The method of  claim 12  wherein the one or more keywords in the aggregate profile for the predicted encounter are keywords in user profiles of the plurality of second users that match keywords in a user profile of the first user. 
     
     
         22 . The method of  claim 12  wherein the one or more keywords in the aggregate profile for the predicted encounter are keywords in user profiles of the plurality of second users that match keywords in a target user profile defined by the first user. 
     
     
         23 . The method of  claim 12  wherein the one or more keywords in the aggregate profile for the predicted encounter are matching keywords in user profiles of the plurality of second users. 
     
     
         24 . The method of  claim 1  wherein the plurality of second users form a first user group of a plurality of user groups identified for the predicted encounter. 
     
     
         25 . The method of  claim 1  wherein the plurality of second users are users identified for the predicted encounter. 
     
     
         26 . The method of  claim 1  further comprising presenting the one or more content recommendations to the first user. 
     
     
         27 . A computing device comprising:
 a communication interface; and   a controller associated with the communication interface and adapted to:
 obtain an aggregate profile for a predicted encounter of a first user, the aggregate profile being based on user profiles of a plurality of second users identified for the predicted encounter of the user; and 
 obtain one or more content recommendations for the first user based on the aggregate profile for the predicted encounter. 
   
     
     
         28 . A computer readable medium storing software for instructing a controller of a computing device to:
 obtain an aggregate profile for a predicted encounter of a first user, the aggregate profile being based on user profiles of a plurality of second users identified for the predicted encounter of the user; and   obtain one or more content recommendations for the first user based on the aggregate profile for the predicted encounter.